A computer network search may be based on strings typed in by an end-user, using a search engine, such as GOOGLE™, YAHOO™, or another string-based web search engine. This type of search technology is focused on relating the meaning of the input strings to known documents that are then ranked by relevance. Though this is powerful in terms of textual information, it tends to be very limiting in terms of trading off attributes.
For instance, when a user types “car” into a string-based web search engine, he may see all sorts of information related to cars, including where he can rent cars and purchase cars. A website link may also be displayed that describes what a car is. When a user reads through all of the documents on the websites returned in search results and displayed by a string-based web search engine, the user may get an idea of the type of car that he is interested in.
Another technology is search based on similar clusters, in which data is sorted in clusters/bins prior to search. A good example of search based on similar clusters is using a car-related search website, such as the Edmunds website, and websites of car dealers. A car-related search website allows a user to select cars out of different overlapping bins, such as an SUV, wagon, sedan, mid-size, van, used, new, make, or model. When a user selects an SUV, the user may choose based upon price range or feature set. In this respect, the user receives a richer “car information” experience with a car search website than with a string-based web search engine. However, with a typical car search website, a user has to go through several car descriptions before finding something that he is satisfied with.